Using Data to Create a Strong Student Experience

Improving use of data analytics in courses and programs creates a more student-centered, responsive experience for non-traditional students.

Over the past few years, tracking and acting on data analytics has become common practice at leading institutions nationwide. From the administrative to the academic, institutions are measuring performance and institutions are becoming responsive to the results. Many institutions are even using data to predict future performance. Data responsiveness doesn’t just contribute to the bottom line, though. Increased use of data can have a significant and positive impact on the student experience, especially for non-traditional learners.

The EvoLLLution (Evo): How can the use of data analytics in the classroom contribute to the creation of value for students—especially given the focus of today’s students on ROI?

Shannon McCarty (SM): The increased use of data analytics is really going to help guide student behavior. It can increase time on task and directly impact ROI, which we know is important to adult students, who are busy and often taking online classes. The implementation of data analytics can help students focus their behaviors.

It can also drive how we create our lessons, how we build activities within the lessons, formative assessments, and just how even the information is presented. Using data analytics allows for a great deal of adaptability.

Evo: Do students enjoy adaptive learning experiences more than the more static week-by week classes where educators are effectively teaching the same material to the entire class?

SM: Yes; students prefer adaptive learning. We’ve been working on an adaptive learning grant and applied it in two different scenarios: One for developmental students in an English class, where we have effectively created a flipped classroom environment, and one for online students.

From the feedback we’ve received from students, it’s clear that they really like the adaptive approach because it does allow them to focus their time and their efforts. It puts them in a very safe learning environment, it creates deeper meaning and then offers the extra attention they need to be successful.

Evo: Building on that, how does this more metric-driven approach compare to the traditional approach to programming when it comes to meeting student expectations?

SM: The more data-driven we become, the more we can meet student expectations. It’s a very different approach, based on leveraging the technology that facilitates high-touch engagement with students. You can provide triggers throughout your courses, or even as students are moving through a course or a program, to create more high-touch interaction, be it between the student or the faculty member or on the student service side, having someone reach out.

The traditional approach was that that students will just enroll, they’ll take courses, and we’ll see how they do. Now it’s really, “What can we put in the hands of the instructors and student services to create more of a high-touch environment for students?”

Evo: What are the most significant roadblocks standing in the way of transitioning to this more student-centered approach to program design and delivery?

SM: Higher education has not used analytics previously; it’s taking that business approach to education and that’s different.

Higher ed institutions are usually fairly slow to change. Sometimes people are worried about what you might find out looking at the analytics. Perhaps you thought you had a fantastic course design and you started really looking at the data, looking at the analytics and you find out that you still have a lot of work to do. It also takes a lot of time to go back and tag your content and analyze it, you have to have someone who knows how to analyze the data. It can be costly as well, but it’s the approach for future generations and it will continue to be implemented.

A lot more schools are getting into the big data arena and looking at actionable data. It’s just going to take some time to get there, and it’s trial and error.

Evo: Is there anything you’d like to add about the capacity for data analytics to create an environment where institutions are better able to provide students value for their educational investment?

SM: We’re at an exciting time with higher ed. Those institutions that are playing with data analytics really understand that this can help guide how they build programs and courses, and how they can make the institution more student-centered. Especially for adult learners, the relevancy aspect issue is important.